Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...

Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...

Prediction of heart disease is very important because it is one of the causes of death around the world. Moreover, heart disease prediction in the early stage plays a main role in the treatment and recovery disease and reduces costs of diagnosis disease and side effects it. Machine learning algorithms are able to identify an effective pattern for diagnosis and treatment of the disease and ident...

Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...

Human performance defines the standard that machine learning systems aspire to in many areas, including learning language. This suggests that studying human cognition may be a good way to develop better learning algorithms, as well as providing basic insights into how the human mind works. However, in order for ideas to flow easily from cognitive science to computer science and vice versa, we n...

Run off resulted from rainfall is the main way of receiving water in most parts of the World. Therefore, prediction of runoff volume resulted from rainfall is getting more and more important in control, harvesting and management of surface water. In this research a number of machine learning and data mining methods including support vector machines, regression trees (CART algorithm), model tree...

   Background & Objective: Hypothyroidism is a prevalent condition in various regions all over the world, including Iran. This study aimed to identify the factors associated with thyroid dysfunctions in Ravansar area, Kermanshah province. Due to hypo and hyperthyroidism diversity and pathogeneses complexity, machine learning was also integrated; it is as an accurate and potent method for the di...